class_docstr: The G2P model evaluation wrapper
  
  Arguments
  ---------
  hparams: dict
      the dictionary from a parsed hyperparameter file
  device: str
      the device identifier
  model_state: dict
      a pre-loaded model state for a "warm start" if applicable
      - could be useful if hyperparameters have changed, but
      the same model can be reused from one run to the next
docstr: Flattens a sequence of words, inserting word separators between them -
  used when word separators are preserved in the phoneme space
  
  Arguments
  ---------
  results: iterable
      a two-dimensional result
  
  Returns
  -------
  result: list
      the concatenated reuslt
docstr_tok: ["Flattens","a","sequence","of","words",",","inserting","word","separators","between","them","-","used","when","word","separators","are","preserved","in","the","phoneme","space","Arguments","--","--","--","--","-","results",":","iterable","a","two-dimensional","result","Returns","--","--","--","-","result",":","list","the","concatenated","reuslt"]
code: def _flatten_results_separated(self, results):
      """Flattens a sequence of words, inserting word separators between them -
      used when word separators are preserved in the phoneme space
  
      Arguments
      ---------
      results: iterable
          a two-dimensional result
  
      Returns
      -------
      result: list
          the concatenated reuslt
      """
      result = []
      for item_result in results:
          for token in item_result:
              result.append(token)
          if item_result and item_result[-1] != self._word_separator:
              result.append(self._word_separator)
      del result[-1]
      return result
  
imports: from hyperpyyaml import load_hyperpyyaml
  from speechbrain.dataio.batch import PaddedBatch
  from speechbrain.lobes.models.g2p.dataio import get_sequence_key
  from speechbrain.utils import hpopt
  from speechbrain.wordemb.util import expand_to_chars
  from train import dataio_prep, load_dependencies
  from types import SimpleNamespace
  from tqdm.auto import tqdm
  import math
  import itertools
  import speechbrain
  import torch
  import sys
  import logging
label_desc: Use image node_id 8 for calling the G2PEvaluator obj's underlying member method code with example usage: obj._flatten_results_separated(results) and returns: result